### 抄録

Chaotic behaviors are characterized mainly by Lyapunov numbers of a dynamic system. In this paper, a new method is proposed, which can control the maximum Lyapunov number of dynamic system that can be represented by Universal Learning Networks (ULNs). The maximum Lyapunov number of a dynamic system can be formulated by using higher order derivatives of ULNs and parameters of ULNs can be adjusted for the maximum Lyapunov number to approach to the target value by the combined gradient and random search method. Based on simulation results, a fully connected ULN with three nodes is possible to display chaotic behaviors.

元の言語 | 英語 |
---|---|

ページ（範囲） | 1702-1707 |

ページ数 | 6 |

ジャーナル | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |

巻 | 2 |

出版物ステータス | 出版済み - 12 1 1998 |

イベント | Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 2 (of 5) - San Diego, CA, USA 継続期間: 10 11 1998 → 10 14 1998 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Control and Systems Engineering
- Hardware and Architecture

### これを引用

*Proceedings of the IEEE International Conference on Systems, Man and Cybernetics*,

*2*, 1702-1707.

**Chaos control using maximum Lyapunov number of universal learning network.** / Hirasawa, K.; Wan, X.; Murata, J.; Hu, J.

研究成果: ジャーナルへの寄稿 › Conference article

*Proceedings of the IEEE International Conference on Systems, Man and Cybernetics*, 巻. 2, pp. 1702-1707.

}

TY - JOUR

T1 - Chaos control using maximum Lyapunov number of universal learning network

AU - Hirasawa, K.

AU - Wan, X.

AU - Murata, J.

AU - Hu, J.

PY - 1998/12/1

Y1 - 1998/12/1

N2 - Chaotic behaviors are characterized mainly by Lyapunov numbers of a dynamic system. In this paper, a new method is proposed, which can control the maximum Lyapunov number of dynamic system that can be represented by Universal Learning Networks (ULNs). The maximum Lyapunov number of a dynamic system can be formulated by using higher order derivatives of ULNs and parameters of ULNs can be adjusted for the maximum Lyapunov number to approach to the target value by the combined gradient and random search method. Based on simulation results, a fully connected ULN with three nodes is possible to display chaotic behaviors.

AB - Chaotic behaviors are characterized mainly by Lyapunov numbers of a dynamic system. In this paper, a new method is proposed, which can control the maximum Lyapunov number of dynamic system that can be represented by Universal Learning Networks (ULNs). The maximum Lyapunov number of a dynamic system can be formulated by using higher order derivatives of ULNs and parameters of ULNs can be adjusted for the maximum Lyapunov number to approach to the target value by the combined gradient and random search method. Based on simulation results, a fully connected ULN with three nodes is possible to display chaotic behaviors.

UR - http://www.scopus.com/inward/record.url?scp=0032307951&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032307951&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0032307951

VL - 2

SP - 1702

EP - 1707

JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

SN - 0884-3627

ER -